Crate subtr_actor 

subtr-actor

subtr-actor is a versatile library designed to facilitate the processes of working with and extracting data from Rocket League replays. Utilizing the powerful boxcars library for parsing, subtr-actor simplifies (or ‘subtracts’, as hinted by its name) the underlying actor-based structure of replay files, making them more accessible and easier to manipulate.

Overview of Key Components

• ReplayProcessor: This struct is at the heart of subtr-actor’s replay processing capabilities. In its main entry point, ReplayProcessor::process, it pushes network frames from the boxcars::Replay that it is initialized with though an ActorStateModeler instance, calling the Collector instance that is provided as an argument as it does so. The Collector is provided with a reference to the ReplayProcessor each time the it is invoked, which allows it to use the suite of helper methods which greatly assist in the navigation of the actor graph and the retrieval of information about the current game state.

• Collector: This trait outlines the blueprint for data collection from replays. The Collector interfaces with a ReplayProcessor, handling frame data and guiding the pace of replay progression with TimeAdvance. It is typically invoked repeatedly through the ReplayProcessor::process method as the replay is processed frame by frame.

• FrameRateDecorator: This struct decorates a Collector implementation with a target frame duration, controlling the frame rate of the replay processing.

Collector implementations

subtr-actor also includes implementations of the Collector trait:

• NDArrayCollector: This Collector implementations translates frame-based replay data into a 2 dimensional array in the form of a ::ndarray::Array2 instance. The exact data that is recorded in each frame can be configured with the FeatureAdder and PlayerFeatureAdder instances that are provided to its constructor (NDArrayCollector::new). Extending the exact behavior of NDArrayCollector is thus possible with user defined FeatureAdder and PlayerFeatureAdder, which is made easy with the build_global_feature_adder! and build_player_feature_adder! macros. The ::ndarray::Array2 produced by NDArrayCollector is ideal for use with machine learning libraries like pytorch and tensorflow.

• ReplayDataCollector: This Collector implementation provides an easy way to get a serializable to e.g. json (though serde::Serialize) representation of the replay. The representation differs from what you might get from e.g. raw boxcars in that it is not a complicated graph of actor objects, but instead something more natural where the data associated with each entity in the game is grouped together.

Examples

Getting JSON

fn get_json(filepath: std::path::PathBuf) -> anyhow::Result<String> {
    let data = std::fs::read(filepath.as_path())?;
    let replay = boxcars::ParserBuilder::new(&data)
        .must_parse_network_data()
        .on_error_check_crc()
        .parse()?;
    Ok(subtr_actor::ReplayDataCollector::new()
        .get_replay_data(&replay)
        .map_err(|e| e.variant)?
        .as_json()?)
}

Getting a ::ndarray::Array2

In the following example, we demonstrate how to use boxcars, NDArrayCollector and FrameRateDecorator to write a function that takes a replay filepath and collections of features adders and returns a ReplayMetaWithHeaders along with a ::ndarray::Array2 . The resulting ::ndarray::Array2 would be appropriate for use in a machine learning context. Note that ReplayProcessor is also used implicitly here in the Collector::process_replay

use subtr_actor::*;

fn get_ndarray_with_info_from_replay_filepath(
    filepath: std::path::PathBuf,
    feature_adders: FeatureAdders<f32>,
    player_feature_adders: PlayerFeatureAdders<f32>,
    fps: Option<f32>,
) -> anyhow::Result<(ReplayMetaWithHeaders, ::ndarray::Array2<f32>)> {
    let data = std::fs::read(filepath.as_path())?;
    let replay = boxcars::ParserBuilder::new(&data)
        .must_parse_network_data()
        .on_error_check_crc()
        .parse()?;

    let mut collector = NDArrayCollector::new(feature_adders, player_feature_adders);

    FrameRateDecorator::new_from_fps(fps.unwrap_or(10.0), &mut collector)
        .process_replay(&replay)
        .map_err(|e| e.variant)?;

    Ok(collector.get_meta_and_ndarray().map_err(|e| e.variant)?)
}

fn get_ndarray_with_default_feature_adders(
    filepath: std::path::PathBuf,
) -> anyhow::Result<(ReplayMetaWithHeaders, ::ndarray::Array2<f32>)> {
    get_ndarray_with_info_from_replay_filepath(
        filepath,
        vec![
            InterpolatedBallRigidBodyNoVelocities::arc_new(0.003),
            CurrentTime::arc_new(),
        ],
        vec![
            InterpolatedPlayerRigidBodyNoVelocities::arc_new(0.003),
            PlayerBoost::arc_new(),
            PlayerAnyJump::arc_new(),
            PlayerDemolishedBy::arc_new(),
        ],
        Some(30.0),
    )
}

Using NDArrayCollector::from_strings

In the second function in the example above, we see the use of feature adders like InterpolatedPlayerRigidBodyNoVelocities. The feature adders that are included with subtr_actor can all be found in the crate::collector::ndarray module. It is also possible to access these feature adders by name with strings, which can be useful when implementing bindings for other languages since those languages may not be able to access rust structs an instantiate them easily or at all.

pub static DEFAULT_GLOBAL_FEATURE_ADDERS: [&str; 1] = ["BallRigidBody"];

pub static DEFAULT_PLAYER_FEATURE_ADDERS: [&str; 3] =
    ["PlayerRigidBody", "PlayerBoost", "PlayerAnyJump"];

fn build_ndarray_collector(
    global_feature_adders: Option<Vec<String>>,
    player_feature_adders: Option<Vec<String>>,
) -> subtr_actor::SubtrActorResult<subtr_actor::NDArrayCollector<f32>> {
    let global_feature_adders = global_feature_adders.unwrap_or_else(|| {
        DEFAULT_GLOBAL_FEATURE_ADDERS
            .iter()
            .map(|i| i.to_string())
            .collect()
    });
    let player_feature_adders = player_feature_adders.unwrap_or_else(|| {
        DEFAULT_PLAYER_FEATURE_ADDERS
            .iter()
            .map(|i| i.to_string())
            .collect()
    });
    let global_feature_adders: Vec<&str> = global_feature_adders.iter().map(|s| &s[..]).collect();
    let player_feature_adders: Vec<&str> = player_feature_adders.iter().map(|s| &s[..]).collect();
    subtr_actor::NDArrayCollector::<f32>::from_strings(
        &global_feature_adders,
        &player_feature_adders,
    )
}

Re-exports

pub use crate::actor_state::*;

pub use crate::collector::*;

pub use crate::constants::*;

pub use crate::error::*;

pub use crate::mechanics::*;

pub use crate::processor::*;

pub use crate::stats::*;

pub use crate::util::*;

Modules

actor_state

ballchasing

collector

constants

error

mechanics

processor

stats

stats_export

util

Macros

attribute_match

Attempts to match an attribute value with the given type.

build_global_feature_adder

Declares a new global feature-adder type and wires it into the ndarray traits.

build_player_feature_adder

Declares a new per-player feature-adder type and wires it into the ndarray traits.

convert_all

Converts a fixed list of values with a caller-supplied error mapper.

convert_all_floats

Converts a fixed list of float-like values using convert_float_conversion_error.

get_attribute_errors_expected

Obtains an attribute from a map and ensures it matches the expected type.

global_feature_adder

Implements the ndarray feature-adder traits for an existing global feature type.

impl_feature_adder

Implements FeatureAdder for a type that already satisfies LengthCheckedFeatureAdder.

impl_player_feature_adder

Implements PlayerFeatureAdder for a type that satisfies LengthCheckedPlayerFeatureAdder.

player_feature_adder

Implements the ndarray feature-adder traits for an existing per-player feature type.